Question

I need a deep learning a code tutorial in Matlab or Python with explanation. I prefer if its matrices related.

Answer 1

To install keras on your machine using PIP, run the following command.

sudo pip install keras

Steps to implement your deep learning program in Keras

1. Load Data.
2. Define Model.
3. Compile Model.
4. Fit Model.
5. Evaluate Model.
6. Tie It All Together.

Program :

# Importing Keras Sequential Model
from keras.models import Sequential
from keras.layers import Dense
import numpy

# Initializing the seed value to a integer.
seed = 7

numpy.random.seed(seed)

# Loading the data set (PIMA Diabetes Dataset)
dataset = numpy.loadtxt('datasets/pima-indians-diabetes.csv', delimiter=",")

# Loading the input values to X and Label values Y using slicing.
X = dataset[:, 0:8]
Y = dataset[:, 8]

# Initializing the Sequential model from KERAS.
model = Sequential()

# Creating a 16 neuron hidden layer with Linear Rectified activation function.
model.add(Dense(16, input_dim=8, init='uniform', activation='relu'))

# Creating a 8 neuron hidden layer.
model.add(Dense(8, init='uniform', activation='relu'))

# Adding a output layer.
model.add(Dense(1, init='uniform', activation='sigmoid'))

# Compiling the model
model.compile(loss='binary_crossentropy',
              optimizer='adam', metrics=['accuracy'])
# Fitting the model
model.fit(X, Y, nb_epoch=150, batch_size=10)

scores = model.evaluate(X, Y)

print("%s: %.2f%%" % (model.metrics_names[1], scores[1] * 100))